AI Agents

A model generates or interprets content. An agent adds an execution loop, tools, state, and stopping or approval rules around model calls. Start with this distinction before comparing agent products.

Read harness material when your question concerns context assembly, tool execution, recovery, or permissions. Builder comparisons are more useful when choosing an interface for composing and operating a workflow.

Specify the source set, permitted actions, expected artifact, and acceptance checks. A final chat message is weak evidence if the task was to change a file, verify a repository, or prepare a cited report.

No. Parallel work helps when tasks can be separated and their results checked. Shared mutable files, duplicated research, and inconsistent assumptions can add coordination cost instead.

Tool access establishes what can be attempted; approval boundaries establish which actions may proceed. Reading a source and sending a message have different consequences even if both use a connector.

Check where the run loses evidence, misinterprets an instruction, or stops recovering from a tool error. Fix the smallest repeatable failure before adding more tools or extending the task.